# -*- coding: utf-8 -*-

from utils.operators.cluster_for_spark_sql_operator import SparkSqlOperator
from jms.dwd.tab.dwd_barscan_centerarrival_dt import jms_dwd__dwd_barscan_centerarrival_dt
from jms.dwd.tab.dwd_barscan_loading_dt import jms_dwd__dwd_barscan_loading_dt
from jms.dwd.oms.dwd_oms_waybill_dt import jms_dwd__dwd_oms_waybill_dt
from jms.dim.dim_network_whole_massage import jms_dim__dim_network_whole_massage
from jms.dim.dim_lmdm_sys_network_distributi import jms_dim__dim_lmdm_sys_network_distributi

jms_dm__dm_cn_export_diff_weight_detail_dt = SparkSqlOperator(
    task_id='jms_dm__dm_cn_export_diff_weight_detail_dt',
    task_concurrency=1,
    pool_slots=2,
    master='yarn',
    name='jms_dm__dm_cn_export_diff_weight_detail_dt_{{ execution_date | date_add(1) | cst_ds }}',
    sql='jms/dm/dm_cn_export_diff_weight_detail/execute.hql',
    executor_cores=2,
    executor_memory='3G',
    email=['yushuo@jtexpress.com','yl_bigdata@yl-scm.com'],
    num_executors=5,  # spark.dynamicAllocation.enabled 为 True 时，num_executors 表示最少 Executor 数
    conf={'spark.dynamicAllocation.enabled'                  : 'true',  # 动态资源开启
          'spark.shuffle.service.enabled'                    : 'true',  # 动态资源 Shuffle 服务开启
          'spark.dynamicAllocation.maxExecutors'             : 12,  # 动态资源最大扩容 Executor 数
          'spark.dynamicAllocation.cachedExecutorIdleTimeout': 60,  # 动态资源自动释放闲置 Executor 的超时时间(s)
          'spark.sql.sources.partitionOverwriteMode'         : 'dynamic',  # 允许删改已存在的分区
          'spark.executor.memoryOverhead'                    : '1G',  # 堆外内存
          'spark.sql.shuffle.partitions'                     : 600,
          },
    yarn_queue='pro',
)

jms_dm__dm_cn_export_diff_weight_detail_dt << [
    jms_dwd__dwd_barscan_centerarrival_dt,
    jms_dwd__dwd_barscan_loading_dt,
    jms_dwd__dwd_oms_waybill_dt,
    jms_dim__dim_network_whole_massage,
    jms_dim__dim_lmdm_sys_network_distributi
]
